Strong evidence from family and twin studies demonstrates that major depressive disorder (MDD) is heritable, yet there has been limited progress in identifying the actual genes involved. A separate, perhaps overlapping set of genes is expected to play a role in individual variation in treatment response in MDD. We seek to characterize genetically, using a large set of markers in many genes, patients who differ in their response to standard antidepressant treatments. Our initial focus was on two sets of genes most likely to play a role in the etiology of major depression. More recently we have expanded our studies to include genetic markers representing every common functional variation in the human genome. We utilize state-of-the-art, high-throughput genotyping methods as well as sophisticated methods of genetic analysis that take into account genetic and non-genetic influences on treatment outcome. In the first years of this project, we completed genotyping 738 markers in a set of 68 candidate genes selected by an expert panel. Results implicated several of these genes in treatment outcome and other genes that contribute to adverse effects. We also discovered genetic markers that help identify those at risk for sexual dysfunction during antidepressant therapy. We also identified potential genetic markers that increase risk of suicidal ideation that may occasionally emerge during antidepressant treatment. Future studies are needed to determine whether individuals who carry such genetic markers may benefit from closer monitoring or alternative treatments. In 2011, we joined a collaboration with investigators from Harvard, the Max Planck Institute Munich, UCSF, and University College London to carry out a meta-analysis of STAR*D along with the two other genome-wide association studies of antidepressant outcome that have been completed, known as MARS and GENDEP. Despite greater power of this combined sample to confer to uncover association with common genetic markers, no genome-wide significant associations were uncovered. We concluded that no common alleles of large effect on antidepressant outcome exist in these samples. In the past year, work led by an extramurally-funded fellow investigated why minority participants in clinical trials like STAR*D drop out of treatment and experience poorer treatment response than non-minorities. The goal here is to boost minority retention in clinical trials and identify genetic markers of treatment response and associated adverse effects, which often vary by ancestry. The research showed that race, ethnicity, genetic ancestry, and other factors affect SSRI treatment response, but genetic African ancestry remains a significant risk factor for poor response, even after other factors are taken into account. We are now using new, high-throughput sequencing methods to test for rarer alleles that may exert larger effects, at least on treatment resistance. Rarer alleles may show larger effects, especially among patients with unusual treatment outcomes. Sequencing studies may uncover alleles that play a major role in a minority of patients. Few patients will carry such alleles, but the genes involved will point to attractive new drug targets. Patients who respond to antidepressant treatment constitute a mixture of true responders, placebo responders, and spontaneous remitters. Patients who fail to respond to multiple treatments may be less heterogeneous, since placebo responders and spontaneous remitters are removed. From over 4,000 patients enrolled in STAR*D, we find that only 10% show treatment resistance that is not explained by non-adherence, comorbid substance use disorder, or other factors, and only 3% are highly treatment-resistant. Sequencing of the coding regions of the genome (exome)has now been completed on 75 treatment-resistant and 25 typically responsive patients. Initial analyses have uncovered some promising leads, but additional studies in larger samples are needed. In the coming year, we will further investigate the genetic basis of treatment-resistant depression in additional samples. These will include patients who respond to novel antidepressants such as ketamine and those referred for electroconvulsive or other neurostimulation therapies.